3D/2D rodent brain extraction using shape model and instance learning

Accurate rodent brain extraction is one of the basic steps for many translational study using Magnetic Resonance Imaging (MRI). In this report, we present a new approach to model the rodent brain variation using non-rigid B-spline image registration for the brain extraction in MRI images. We mode...

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Main Author: Ling, Chen
Other Authors: Lin Zhiping
Format: Final Year Project
Language:English
Published: 2017
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Online Access:http://hdl.handle.net/10356/72200
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-722002023-07-07T16:35:37Z 3D/2D rodent brain extraction using shape model and instance learning Ling, Chen Lin Zhiping School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Accurate rodent brain extraction is one of the basic steps for many translational study using Magnetic Resonance Imaging (MRI). In this report, we present a new approach to model the rodent brain variation using non-rigid B-spline image registration for the brain extraction in MRI images. We model the shape and appearance with the B-spline parameters together with a mean brain image. Followed by a method using multi-expert, we refine the brain extraction region. Compared with the image-based template model using cross-correlation, the performance for rodent brain extraction has shown much improvement on one data set while maintaining the similar yet more consistent performance for another. Both template based methods however outperform the voxel based method (3D PCNN) and a modified BET version for rodent brain extraction. Bachelor of Engineering 2017-05-29T09:02:29Z 2017-05-29T09:02:29Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/72200 en Nanyang Technological University 48 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Ling, Chen
3D/2D rodent brain extraction using shape model and instance learning
description Accurate rodent brain extraction is one of the basic steps for many translational study using Magnetic Resonance Imaging (MRI). In this report, we present a new approach to model the rodent brain variation using non-rigid B-spline image registration for the brain extraction in MRI images. We model the shape and appearance with the B-spline parameters together with a mean brain image. Followed by a method using multi-expert, we refine the brain extraction region. Compared with the image-based template model using cross-correlation, the performance for rodent brain extraction has shown much improvement on one data set while maintaining the similar yet more consistent performance for another. Both template based methods however outperform the voxel based method (3D PCNN) and a modified BET version for rodent brain extraction.
author2 Lin Zhiping
author_facet Lin Zhiping
Ling, Chen
format Final Year Project
author Ling, Chen
author_sort Ling, Chen
title 3D/2D rodent brain extraction using shape model and instance learning
title_short 3D/2D rodent brain extraction using shape model and instance learning
title_full 3D/2D rodent brain extraction using shape model and instance learning
title_fullStr 3D/2D rodent brain extraction using shape model and instance learning
title_full_unstemmed 3D/2D rodent brain extraction using shape model and instance learning
title_sort 3d/2d rodent brain extraction using shape model and instance learning
publishDate 2017
url http://hdl.handle.net/10356/72200
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